395 research outputs found
Romania: an ambivalent parliamentary opposition
No full textIn recent years an increasing number of scholars have analyzed the workings of the Romanian Parliament focusing on individual legislative behavior topics ranging from voting cohesion (Coman 2012; Gherghina and Chiru 2014) toco-sponsorship patterns (Neamtu 2011; Chiru and Neamtu 2012) and constituency service (Chiru 2015). Another substantive body of scholarship concentrated on the MPs' attitudes, more specifically on their views on party discipline (Stefan et al 2012), representation roles (Chiru and Enyedi 2015), or their willingness to stand for re-election (Chiru et al 2013). In contrast, little work has been done on opposition behavior in Romania. The scarce scholarship looked mostly at no confidence motions and investiture votes (Stan and Vancea 2014; Stan 2015; Chiva 2015).
This chapter makes a step in this direction and seeks to understand the voting behavior, legislative initiative and scrutiny of the opposition in Romania between 2007 and 2011
AMOVA for grouping of populations estimated using Φ-statistics based on control region sequence for chiru (<i>Pantholops hodgsonii</i>).
No full text<p>AMOVA for grouping of populations estimated using Φ-statistics based on control region sequence for chiru (<i>Pantholops hodgsonii</i>).</p
sj-zip-1-eup-10.1177_14651165211053439 - Supplemental material for Introducing COMEPELDA: Comprehensive European Parliament electoral data covering rules, parties and candidates
No full textSupplemental material, sj-zip-1-eup-10.1177_14651165211053439 for Introducing COMEPELDA: Comprehensive European Parliament electoral data covering rules, parties and candidates by Thomas Däubler, Mihail Chiru and Silje SL Hermansen in European Union Politics</p
Mismatch distributions.
No full text<p>Mismatch distributions of mtDNA control region for A) chiru (<i>Pantholops hodgsonii</i>) and B) Tibetan gazelle (<i>Procapra picticaudata</i>). The parameters of the goodness-of-fit test to the model of sudden expansion <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060712#pone.0060712-Rogers1" target="_blank">[52]</a> are: sum of squared deviations (SSD), 0.0049 for the chiru (<i>p</i> = 0.37), and 0.0239 for the Tibetan gazelle (<i>p</i> = 0.224); r, raggedness index, 0.0024 for the chiru (<i>p</i> = 0.6), and 0.0216 for the Tibetan gazelle (<i>p</i> = 0.047).</p
The Social Cost-of-Living: Welfare Foundations and Estimation
No full textWe present a new class of social cost-of-living indices and a nonparametric framework for estimating these and other social cost-of-living indices. Common social cost-of-living indices can be understood as aggregator functions of approximations of individual cost-of-living indices. The Consumer Price Index (CPI) is the expenditure-weighted average of first-order approximations of each individual’s cost-of-living index. This is troubling for three reasons. First, it has not been shown to have a welfare economic foundation for the case where agents are heterogeneous (as they clearly are.) Second, it uses an expenditure-weighted average which downweights the experience of poor households relative to rich households. Finally, it uses only first-order approximations of each individual’s cost-of-living index, and thus ignores substitution effects. We propose a “common-scaling” social cost-of-living index, which is defined as the single scaling to everyone’s expenditure which holds social welfare constant across a price change. Our approach has an explicit social welfare foundation and allows us to choose the weights on the costs of rich and poor households. We also give a unique solution for the welfare function for the case where the weights are independent of household expenditure. A first order approximation of our social cost-of-living index nests as special cases commonly used indices such as the CPI. We also provide a nonparametric method for estimating second-order approximations (which account for substitution effects).Inflation, Social cost-of-living, Demand, Average derivatives
The Social Cost-of-Living: Welfare Foundations and Estimation
No full textWe present a new class of social cost-of-living indices and a nonparametric framework for estimating these and other social cost-of- living indices. Common social cost-of-living indices can be understood as aggregator functions of approximations of individual cost-of-living indices. The Consumer Price Index (CPI) is the expenditure-weighted average of first-order approximations of each individual’s cost-of-living index. This is troubling for three reasons. First, it has not been shown to have a welfare economic foundation for the case where agents are heterogeneous (as they clearly are.) Second, it uses an expenditure-weighted average which downweights the experience of poor households relative to rich households. Finally, it uses only first-order approximations of each individual’s cost-of-living index, and thus ignores substitution effects. We propose a “common-scaling” social cost-of-living index, which is defined as the single scaling to everyone’s expenditure which holds social welfare constant across a price change. Our approach has an explicit social welfare foundation and allows us to choose the weights on the costs of rich and poor households. We also give a unique solution for the welfare function for the case where the weights are independent of household expenditure. A first order approximation of our social cost-of- living index nests as special cases commonly used indices such as the CPI. We also provide a nonparametric method for estimating second- order approximations (which account for substitution effects).Inflation, Social cost-of-living, Demand, Average Derivatives
Phylogenetic relationships.
No full text<p>Bayesian inferred (BI) trees among the mitochondrial control region haplotypes for A) chiru (<i>Pantholops hodgsonii</i>), and B) Tibetan gazelle (<i>Procapra picticaudata</i>). Posterior possibilities are indicated next to nodes.</p
Haplotype networks.
No full text<p>TCS generated haplotype networks of A) chiru (<i>Pantholops hodgsonii</i>), and B) Tibetan gazelle (<i>Procapra picticaudata</i>) based on the mitochondrial DNA sequences. Numbers in the parentheses denote the haplotype frequencies.</p
D5.3 Support and feedback services version 1.5
No full textTrausan-Matu, S., Dessus, P., Rebedea, T., Loiseau, M., Dascalu, M., Mihaila, D., Braidman, I., Armitt, G., Smithies, A., Regan, M., Lemaire, B., Stahl, J., Villiot-Leclercq, E., Zampa, V., Chiru, C., Pasov, I., & Dulceanu, A. (2010). D5.3 Support and feedback services version 1.5. LTfLL-project.This report presents Version 1.5 of the Learning support and feedback services (delivering recommendations based on interaction analysis and on students’ textual production) that can be integrated within an e-learning environment.The work on this publication has been sponsored by the LTfLL STREP that is funded by the European Commission's 7th Framework Programme. Contract 212578 [http://www.ltfll-project.org
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